Blog Archives

apply lapply rapply sapply functions in R

March 18, 2016
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apply lapply rapply sapply functions in R

As part of Data Science with R, this is third tutorial after basic data types,control structures in r.One of the issues with for loop is its memory consumption and its slowness in executing a repetitive task at hand. Often dealing with large data and iterating it, for loop is not advised. R...

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Control Structures Loops in R

February 27, 2016
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Control Structures Loops in R

As part of Data Science tutorial Series in my previous post I posted on basic data types in R. I have kept the tutorial very simple so that beginners of R programming  may takeoff immediately. Please find the online R editor at the end of the post...

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Principal Component Analysis using R

February 27, 2016
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Principal Component Analysis using R

Curse of Dimensionality:One of the most commonly faced problems while dealing with data analytics problem such as recommendation engines, text analytics is high-dimensional and sparse data. At many times, we face a situation where we have a large set of features and fewer data points, or we have data with very high feature vectors. In such scenarios,...

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Basic Data Types in r

February 16, 2016
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As part of tutorial series on Data Science with R from Data Perspective, this first tutorial introduces the very basics of R programming language about basic data types in R.What we learn:Assignment OperatorNumericIntegerComplex numberlogicalCharacterFactorVectorData FrameAfter the end of the chapter, you are provided with R console so that you can practice what you have learnt in this chapter.R...

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Data Science with R

December 24, 2015
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Data Science with R

As R programming language becoming popular more and more among data science group, industries, researchers, companies embracing R, going forward I will be writing posts on learning Data science using R. The tutorial course will include topics on data types of R, handling data using R, probability theory, Machine Learning, Supervised – unSupervised learning, Data Visualization using R,...

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Item Based Collaborative Filtering Recommender Systems in R

November 18, 2015
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Item Based Collaborative Filtering Recommender Systems in R

In the series of implementing Recommendation engines, in my previous blog about recommendation system in R, I have explained about implementing user based collaborative filtering approach using R. In this post, I will be explaining about basic implementation of Item based collaborative filtering recommender systems in r. Intuition:

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Data Mining Standard Process across Organizations

October 18, 2015
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Data Mining Standard Process across Organizations

Recently I have come across a term, CRISP-DM - a data mining standard. Though this process is not a new one but I felt every analyst should know about commonly used Industry wide process. In this post I will explain about different phases involved in creating a data mining solution. CRISP-DM, an acronym for Cross Industry Standard...

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Introduction to Logistic Regression with R

October 6, 2015
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Introduction to Logistic Regression with R

In my previous blog I have explained about linear regression. In today’s post I will explain about logistic regression.         Consider a scenario where we need to predict a medical condition of a patient (HBP) ,HAVE HIGH BP or NO HIGH BP, based on some observed symptoms – Age, weight, Issmoking, Systolic...

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Exposing R-script as API

April 8, 2015
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Exposing R-script as API

R is getting popular programming language in the area of Data Science. Integrating Rscript with web UI pages is a challenge which many application developers are facing. In this blog post I will explain how we can expose R script as an API, using rApache and Apache webserver. rApache is a project supporting web...

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Regression Analysis using R

October 4, 2014
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Regression Analysis using R

What is a Prediction Problem?A business problem which involves predicting future events by extracting patterns in the historical data. Prediction problems are solved using Statistical techniques, mathematical models or machine learning techniques.For example: Forecasting stock price for the next week, predicting which football team wins the world cup, etc.What is Regression analysis, where is it applicable?While dealing with...

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